Method and structure for mitigating instrumentation differences

ABSTRACT

A system for mitigating instrumentation differences in laboratory instruments includes one or more groups of laboratory instruments in communication with a normalization server over a network. Each group of instruments communicates output data to the normalization server which then presents normalized data to the groups of laboratory instruments. Various exemplary embodiments of the system and associated methods are provided.

TECHNICAL FIELD

In general, the present invention relates to instrumentation dataanalysis, and in particularly, to a method and device for mitigatinginstrumentation differences in laboratory equipment.

BACKGROUND OF THE INVENTION

Generally, data outputs from a laboratory instrument testing of asubject sample may be utilized to monitor the performance of theinstrument or to provide a comparison set of results for the subjectbeing tested. Specifically, the subject sample being tested can includea standardized external quality control sample distributed by a testingorganization or an individual patient sample to be tested and analyzed.For example, if the subject sample is a standardized external qualitycontrol sample, the test results from the instrument allow thelaboratory to ensure that the instrument is properly functioning bycomparing the instrument data with peer group results of the samesample. Similarly, if the subject sample is from an individual patient,one or more tests provide a comparison set of data to measure theprogress of the patient. With either type of subject sample, the resultsfrom the test are critical to the operation of the testing laboratory.Moreover, the subject testing can be conducted by one or moreinstruments to form a laboratory testing group.

With regard to the testing of a external quality control sample, aconventional method of control group testing entails testing anddirectly comparing the results to a peer group becomes deficient if thepeer group is too small. For example, if a group of laboratoryinstruments testing a proficiency sample includes data from only eightinstruments, the relatively small number of instrument results do notprovide an adequate peer group to construct a proper range of expectedresults. Accordingly, in such a scenario, it would be advantageous toutilize a larger peer group, such as 400 or 500 instruments from aplurality of laboratories, to develop a proper range of results.However, under the conventional method, differences between theinstruments, in the form of calibration differences, statisticalbehavior differences and/or test method differences, can yielddifferences between the laboratory group results and the peer groupresults. Thus, the conventional method of a direct comparison betweenthe results of the two groups could be either impossible or erroneous.

With regard to the testing of a patient subject sample, the conventionalmethod of testing and directly comparing the data results between afirst and second sample can become deficient if the patient group ismobile and there are differences between the laboratory instruments.Specifically, a patient sample may be tested by a first group oflaboratory instruments yielding a first set of results. If a second testis conducted by a second group of laboratory instruments, differencesbetween the instruments of the two groups may cause a reviewer tobelieve there is a larger discrepancy between the results then thereactually is.

For example, a first test of a patient sample indicates that the amountof a substance in the patient test sample was 100. If the second testconducted by another laboratory group indicates that the amount of thesubstance in the patient sample is 384, a direct comparison of the tworesults would indicate that the patient sample had a substantialincrease in the amount of the substance present. However, it could bepossible that the actual difference in the amount of the substance inthe sample is minimal and that large difference is due primarily to thedifferences (e.g. calibration differences) between the two laboratoryinstrument groups. Accordingly, the conventional method of a directcomparison would cause an improper analysis.

Thus, there is a need for a method and device for facilitating thecomparison of laboratory group results with peer group quality controlresults by mitigating differences in the instruments. Additionally,there is a need for a method and device allowing patient sample resultsto be normalized for comparison by reducing differences between thegroups.

SUMMARY OF THE INVENTION

The present invention satisfies the above-described need by providing amethod and system for mitigating differences in laboratory instrumentoutputs by the normalization of the laboratory instrument output data inaccordance with a control group.

Generally described, the present invention provides a method fornormalizing a group of laboratory instruments. In accordance with themethod, data indicative of control specimen outputs is obtained for thegroup of laboratory instruments, and the data is normalized according toa control group.

In another aspect of the present invention, a method for normalizing twoor more groups of laboratory instruments is provided. In accordance withthe method, a first of the two or more groups of laboratory instrumentscontrol specimen outputs is obtained, a second of the two or more groupsof laboratory instruments control specimen outputs is obtained, and thecontrol specimen outputs from the first and second groups of laboratoryinstruments are normalized.

In a further aspect of the present invention, a system for normalizinggroups of laboratory instruments is provided. The system includes one ormore groups of laboratory instruments and a normalization server incommunication with the groups of laboratory instruments. Additionally,the groups of laboratory instruments send data indicative of outputs tothe normalization system and the normalization system outputs normalizedoutputs to the groups of laboratory instruments.

In yet another aspect of the present invention, a method forstandardizing instrument results from a plurality laboratory instrumentsis provided. In accordance with the method, testing specimen data isobtained from a first of a group of laboratory instruments, the firstlaboratory instrument testing specimen data is normalized according to afirst normalization curve, and the first laboratory instrument data isadjusted according to the first normalization curve.

By normalizing the output from a laboratory group, the present inventionreduces the statistical differences between two or more laboratory groupresults and allows meaningful data analysis.

BRIEF DESCRIPTION OF THE DRAWING

The present invention is described in detail below with reference to theattached drawing figures, wherein:

FIG. 1 is a block diagram illustrating the interaction between one ormore groups of laboratory instruments and a normalization server inaccordance with the teachings of the present invention;

FIG. 2 is a flow diagram of a preferred normalization setup methodimplemented by a normalization server in accordance with the presentinvention;

FIG. 3 is a flow diagram of a preferred normalization usage methodimplemented by a normalization server in accordance with the presentinvention;

FIG. 4 is a chart illustrating a comparison of output results from alaboratory group tests and output values from a control group;

FIG. 5 is illustrative of a line fit plot applied to the laboratorygroup test output of FIG. 3; and

FIG. 6 is a chart illustrating a comparison of the output results from alaboratory group test and output value from a control group of FIG. 3and the normalized laboratory group outputs in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a method and device for mitigatinginstrumentation differences in laboratory equipment outputs bynormalizing the output from the group of laboratory instruments to acontrol group. Preferably, the present invention is implemented in acomputing environment commensurate with the number of laboratoryinstruments in the system and the quantity of data being normalized. Theinvention is operable with numerous general purpose or special purposecomputing system environments. Examples of well known computing systemsthat may be suitable for use with the invention include personalcomputers, server computers, hand-held or lap top devices,multiprocessor systems, network personal computers, minicomputers, andmainframe computers. As would be readily understood by someone skilledin the art, additional computing environments are within the scope ofthe present invention.

FIG. 1 is a block diagram illustrative of the normalization system ofthe present invention, designated generally by the reference number 10.The normalization system 10 includes one or more laboratory instrumentgroups 12 in communication with a normalization server 14 via acommunications network 16.

Preferably, each laboratory instrument group 12 includes a laboratoryinformation system (LIS) 18, which is direct communication with one ormore laboratory instruments 20. As would be readily understood, thelaboratory instrument groups 12 may be remote from each other and fromthe normalization server 14. Additionally, the laboratory instruments 20connected to the LIS 18 may also be remote from each other and from theLIS 18. Moreover, the laboratory instruments 20 may include identicalinstruments from the same manufacturer, different instruments from thesame manufacturer, or instruments from a variety of manufacturers.Preferably, the normalization server includes one or more computingdevices to carry out the functions of the normalization server inaccordance with the present invention.

Preferably, the network 16 includes an Internet-based network, with thenormalization server 14 linked to the groups of laboratory instrumentsvia a web site interface. As would be understood, the network caninclude any variety and/or combination of Local Area Networks (LAN) orWide Area Networks (WAN) to facilitate communication between thelaboratory groups and the normalization server. Additionally, thenetwork 16 may include a dedicated communications link, such as dial-uptelephone modem connection, between the groups of laboratory instruments12 and the normalization server 14.

FIGS. 2 and 3 are flow diagrams of a preferred normalization methodimplemented by the normalization server in accordance with the presentinvention. The present invention utilizes this procedure to establishnormalization curves for known ranges of results and utilize thes curvesfor future external quality control testing and patient sample testing.Preferably, the normalization method is characterized into anormalization setup portion (FIG. 2) and a normalization usage portion(FIG. 3). The normalization setup portion preferably entails thenormalization server receiving test control specimens outputs from oneor more groups of laboratory instruments and generating a normalizationcurve for each instrument. Accordingly, the normalization usage portionentails the normalization server receiving test data (either externalquality control data or patient sample data) and normalizing the dataaccording to the individual normalization curve for the testinginstrument.

FIG. 2 is a flow diagram of a preferred normalization setup method inaccordance with the present invention. As a general rule, laboratoryinstrument groups must constantly test and analyze test controlspecimens from external quality control organization. At S21, thenormalization server obtains outputs from one or more groups oflaboratory instruments testing control specimens. Preferably, thenormalization server can receive the laboratory instrument outputs in avariety of manners. In a first embodiment, the normalization serverincludes an Internet-based web site which receives data from each groupof laboratory instruments. In such an embodiment, the LIS (FIG. 1) fromeach group communicates with the normalization server and sends theoutput data from each laboratory instrument in a manner which isformatted to facilitate normalization. Alternatively, the web site mayinclude a manual input screen that allows the data to be manuallyentered via the web site.

In a second embodiment, a direct communications link, such as atelephone modem connection, is established by the LIS or thenormalization server for the purpose of transferring the output data.Additionally, prior to sending the laboratory instrument output data tothe normalization server, the LIS may format the data in a manner tofacilitate its processing alternatively, a graphical interface may beestablished between the LIS and the normalization server, such as aninput screen, to allow the manual entry of the output data over thecommunications link to the normalization server. In a third embodiment,the output from the laboratory instrument group may be physically sentto the normalization server provider and entered manually via aplurality of data input methods. As would be understood, alternativedata transfer embodiments or a combination of the above mentionedembodiments are within the scope of the present invention.

Once the test specimen output data has been obtained by thenormalization server at S21, the normalization server calculates andstores normalization curves for each laboratory instrument beingnormalized at S22. Preferably, the normalization server utilizes avariety of normalization methods dependant on the output data and thetype of normalization desired to construct the normalization curve. Forexample, in a first embodiment the normalization server utilizes a linerregression method to normalize the data. In a second embodiment, thenormalization server utilizes a nonlinear regression method. In a thirdembodiment, the normalization server applies a spline to normalize thedata.

Preferably, the normalization server receives the group instrumentcontrol specimen data and the control group data for the same controlspecimen and applies the variety of normalization methods to constructnumerous normalization curves. Then, the normalization server measuresthe relative error between the actual data points and the normalizedcurve. For example, assume data from a group of laboratory instrumentsfollows a generally non-linear trend. As the data is received, thenormalization server would utilize a linear regression, a non-linearregression, a spline and any other normalization method to map the datapoints as a curve. Because the data is generally non-linear, however, itis likely that the linear regression would have a greater curve errorthan the non-linear regression curve. Generally, curve error can bedefined as the difference in values from an actual data point and thecalculated data point of the curve.

Accordingly, the normalization server would measure the curve error foreach of the generated curves and select the curve with the least averagecurve error per data point. Alternatively, the normalization server mayselect the curve with the least cumulative curve error for all the datapoints. Moreover, the group of laboratory instruments may also designatea default type of normalization method irrespective of the curve erroranalysis. Once a preferred normalization curve is constructed, thenormalization saves the curve for future use. As would be readilyunderstood, the determination by the normalization server of a bestfitting curve may utilize additional normalization methods and mayutilize additional statistical calculations (e.g. eliminating extremedata points). All are within the scope of the present invention.

FIG. 3 is a flow diagram of a preferred normalization usage method inaccordance with the present invention. Once the normalization setupmethod has been executed (FIG. 2), the normalization server utilizes theindividual curve for each instrument to normalize output data. At S23,the normalization server obtains outputs from one or more groups oflaboratory instruments testing specimens which can be external qualitycontrol specimens or patient testing samples. Similar to the obtainingstep illustrated at S21, the normalization server can obtain the testingspecimen data from the laboratory instruments or LIS in a variety ofmanners.

Once the testing data has been obtained at S23, the data is normalizedaccording to the previously stored normalization curve for eachinstrument at S24. Preferably, the normalization server recalls thecalculated normalization curve and maps the inputted data according tothe preferred curve. Alternatively, the normalization server may recallall the calculated normalization curves, and maps the data into all thecurves. Accordingly, a determination of the best curve for the specificdata points may be selected according to curve error or user choice atthat point. All are considered within the scope of the presentinvention.

Once the output data has been normalized according to the normalizationcurves at S24, the normalization server outputs the normalized data toone or more groups of laboratory instruments at S26. Dependant on theneeds of each group of laboratory instruments, the outputting step canencompass one or more methods. In a first embodiment, the normalizationserver displays the normalized output by group of laboratory instrumentson a central network for access by the specific group of laboratoryinstruments or by the entire network. In a second embodiment, thenormalization server outputs the data directly via a network or a directcommunication line to the LIS (FIG. 1) of the laboratory instrumentgroup. In a third embodiment, the normalization server outputs thenormalized data to a memory for archiving purposes or for latertransmittal to the laboratory instrument group. Additionally, thenormalization server may utilize any combination of the outputtingembodiments to relay the outputted data in more than one manner.

FIGS. 4–6 are charts and graphs illustrating the “mapping” of resultsfrom a group of laboratory instruments into a control group of resultsin accordance with the methods and structures of the present invention.With reference to FIG. 4, chart 28 illustrates outputs for fivespecimens from a group of laboratory instruments in a second column 30and outputs for the same specimen from a control group in a third column32. As can be seen, a direct comparison of the results from thelaboratory instrument outputs and the control group outputs yields a bigdiscrepancy in values. For example, the output results for specimen 1 inrow 34 indicate that the laboratory group result is “98”, while thecontrol group result for the same specimen is “254”. Accordingly, theresulting difference between the two groups appears to be 156. Likewise,a comparison of rows 36–42 discloses apparent differences of 103, 244,233 and 73 respectively. Under a conventional analysis, the results fromthe group 30 would be considered erroneous or incompatible with thecontrol group 32. However, the present invention allows the lab groupresults to be rectified by a mapping of the group of laboratory resultsinto the control group results.

FIG. 5 is illustrative of a line fit plot 44 applied to the group oflaboratory results (FIG. 4) to map the data into the control groupresults in accordance with the present invention. Specifically, based onthe application of a linear regression method, an equation ofy=2.63x+10.4 is calculated to be a preferred normalization curve in thenormalization setup method (FIG. 2). As illustrated in FIG. 5, thecorresponding line 44 generates five data points, 46–54, correspondingto the original laboratory group results. For example, data point 46corresponds to the fifth specimen result (column 42 of FIG. 4) which is“34” on the x-axis of the line fit plot 44. Additionally, the data point46 indicates the mapped value corresponding to the control group resultsis “100”, allowing the two groups of results to be better compared.

FIG. 6 is a chart 56 illustrating the original laboratory groupinstrument outputs in a second column 58, the outputs of a control groupin a third column 60, and the normalized outputs of the laboratoryinstrument outputs in a fourth column 62. As illustrated in rows 64–72,the normalized values of the laboratory instrument outputs 62 are muchcloser to the control group values 60, allowing a better comparison ofthe data. For example, the value for specimen 1 in column 64 indicatesthat the original lab result was “98” while the control group for thespecimen was “254”. As mapped by the method and structure of the presentinvention, however, the normalized value is “268”, better reflecting theactual differences in testing values between the laboratory group andthe control group.

The system and method of the present invention can be implemented in avariety of testing embodiments. In a first embodiment, a group oflaboratory instruments run tests on a external quality control specimenwhich is provided by a testing facility. As would be understood, toprovide quality control testing of the particular instruments, theresults from the laboratory group are compared to a peer group runningtests on specimen samples originating from the same lot. However,statistical differences between the instruments (especially if thegroups have instruments made by different manufacturers) may cause theoutputs to vary significantly. In a conventional testing system, theresults typically cannot be compared and consequently, the laboratoryinstrument groups cannot utilize the larger common peer group. Incontrast, however, the present invention generates normalization curvesallowing the laboratory instrument group results to be normalized withthe control group output by utilizing normalization curves calculatedfrom previous external quality control test specimen data. This methodallows a laboratory instrument group facilitator to compare its outputdata to a larger peer group because differences between groups can bemitigated. Moreover, the mapping of the laboratory output allows thelaboratory instrument group to add their data to the peer group as well.

In an alternative embodiment, the method and device of the presentinvention may also be utilized to provide direct comparison of labresults from two or more laboratory instrument groups. For example, alaboratory patient may have a series of tests conducted at a firstlaboratory group and the same series of tests conducted at a secondlaboratory group. If the laboratory testing groups have statisticaldifferences in their outputs, the conventional monitoring methodprevents a meaningful analysis of the patient's progress. In contrast,the present invention allows the second group outputs to be normalizedwith the first group outputs for a direct comparison. Again, theinstrumentation differences between the laboratory group results aremitigated, which is beneficial for a mobile patient.

In yet another embodiment, the method and device of the presentinvention allows an individual laboratory group to map a chain oflaboratory instruments outputs according to a standardized output valueas the outputs are generated. In this embodiment, a LIS (FIG. 1) withinthe group of laboratory instruments receives a desired value range inwhich to report the outputs from its laboratory instruments. As the LISreceives outputs from the various laboratory instruments in the group,it normalizes the outputs according to the desired value range prior tooutputting the output from the group. Thus, the normalizingfunctionality is built into the LIS for real time processing. As wouldbe readily understood, the normalized output from the LIS could then befurther implemented in other normalization functions such as thosedescribed in the first and second embodiments.

In general, the normalization system of the present invention allowsgroups of laboratory instruments to submit outputs indicative of thelaboratory instrument testing results to the normalization server andhave the outputs normalized according to a control group. The normalizedoutputs can then be utilized to compare the current results with aprevious test and/or to calibrate the group of laboratory instrumentsaccording to a peer group. Additionally, while many program languagescould be used to create the objects and functions of the presentinvention, the present invention is preferably coded by anobject-oriented language such as Microsoft Corporation's “VISUAL C++®”OR “VISUAL BASIC®” programming languages.

It will be understood that certain features and subcombinations are ofutility and may be employed without reference to other features andsubcombinations. This is contemplated by and is within the scope of theclaims.

Since many possible embodiments may be made of the invention withoutdeparting from the scope thereof, it is to be understood that all matterherein set forth or shown in the accompanying drawings is to beinterpreted as illustrative, and not in a limiting sense.

1. A system for normalizing groups of laboratory instruments, the systemcomprising: one or more groups of laboratory instruments; and anormalization server in communication with the groups of laboratoryinstrument, wherein the groups of laboratory instruments comprise alaboratory information system coupled to individual laboratoryinstruments and in communication with the normalization server andwherein the groups of laboratory instruments send data indicative ofoutputs to the normalization system, and wherein the normalizationsystem outputs normalized outputs to the groups of laboratoryintruments.